Center of Excellence for Learning in Education, Science and Technology A National Science Foundation Science of Learning Center

Peer-Reviewed Publications 2011

  1. Ames, H., Mingolla, E., Sohail, A., Chandler, B., Gorchetchnikov, A., Léveillé, J., Livitz, G., and Versace, M. (2011). New frontiers in whole brain modeling. IEEE Magazine, Engineering in Medicine and Biology Special NEST Issue.
  2. Amis, G.P., Carpenter, G.A., Ersoy, B., and Grossberg, S. (2011). Cortical learning of recognition categories: A resolution of the exemplar vs prototype debate.
  3. Barbas, H., Zikopoulos, B., and Timbie, C. (2011). Sensory pathways and emotional context for action in primate prefrontal cortex. Biological Psychiatry, 69, 1133-1139.
  4. Brumberg, J. S., Wright, E. J., Andreasen, D. A., Guenther, F., and Kennedy, P. R (2011). Classification of intended phoneme production from chronic intracortical microelectrode recordings in speech motor cortex. Frontiers in Neuroprosthetics, 5.
  5. Bunce, J. and Barbas, H. (2011). Prefrontal pathways target excitatory and inhibitory systems in memory-related medial temporal cortices. NeuroImage, 55, 1461-1474.
  6. Buschman, T.J., Denovellis, E.L., Diogo, C., Bullock, D., and Miller, E.K. (2011). Dynamic networks in frontal cortex support flexibility to switch between rules.
  7. Buschman, T.J., Siegel, M., Roy, J.E. and Miller, E.K. (2011). Neural substrates of cognitive capacity limitations. Proceedings of the National Academy of Sciences, 108(27), 11252-5.
  8. Cao, B., Yazdabakhsh, A., and Mingolla, E. (2011). The effect of contrast intensity and polarity in the achromatic watercolor effect. Journal of Vision, 11, 1-8.
  9. Cao, Y., Grossberg, S., and Markowitz, J. (2011). How does the brain rapidly learn and reorganize invariant object representations in inferior temporal cortex? Neural Networks, 24, 1050-1061.
  10. Carpenter, G.A. and Ravindran, A.K. (2011). Searching the sky with CONFIGR-STARS. Neural Networks, 24, 208-216.
  11. Chandler, B. and Grossberg, S. (2011). Joining distributed pattern processing and homeostatic plasticity in recurrent on-center off-surround shunting networks: Noise, saturation, short-term memory, synaptic scaling, and BDNF. Neural Networks.
  12. Cutsuridis, V. (2011). Origins of a repetitive and co-contractive pattern of muscle activation in Parkinson’s disease. Neural Networks.
  13. Cutsuridis, V. (2011). GABA inhibition modulates NMDA-R mediated spike timing dependent plasticity (STDP) in a biophysical model. Neural Networks, 24, 29-42.
  14. Cutsuridis, V. (2011). A modeling study on how theta-burst inhibition affects the NMDA-R mediated spike timing-dependent plasticity in the presence of triplets and quadruplets.
  15. Cutsuridis, V. and Hasselmo, M. (2011). Spatial memory sequence encoding and replay during modeled theta and ripple oscillations.
  16. Cutsuridis, V. and Hasselmo, M. (2011). GABAergic modulation of gating, timing and theta phase precession of hippocampal neuronal activity during theta oscillations.
  17. Cutsuridis, V., Heida, C., Duch, W., and Doya, K. (2011). Neural Networks, Special Issue on Neural models of brain disorders.
  18. Doon, J., Getty, D., Mingolla, E., and Wolfe, J. (2011). Searching simulated lungs in 3D with stereoscopic volume rendering. Journal of Vision, 11, 1335.
  19. Foley, N., Grossberg, S., and Mingolla, E. (2011). Neural dynamics of object-based multifocal visual spatial attention and priming: Object cueing, useful-field-of-view, and crowding. Cognitive Psychology.
  20. Franklin, D. and Grossberg, S. (2011). How multiple brain systems cooperate during normal and amnesic conditioning and memory: Amygdala, hippocampus, amnesia, and neurotrophins.
  21. Franklin, D.J. and Grossberg, S. (2011). A neural model of normal and abnormal learning and memory: Adaptively timed conditioning, hippocampus, amnesia, neurotrophins, and consciousness.
  22. Gori S., Giora E., Yazdanbakhsh A., and Mingolla E. (2011). A new motion illusion based on competition between two kinds of motion processing units: The Accordion-Grating.
  23. Grossberg, S. and Chandler, B. (2011). Joining distributed pattern processing and homeostatic plasticity in recurrent on-center off-surround shunting networks: Noise, saturation, short-term memory, synaptic scaling, and BDNF.
  24. Grossberg, S. and Kazerounian, S. (2011). Laminar cortical dynamics of conscious speech perception: Neural model of phonemic restoration using subsequent context in noise. Journal of the Acoustical Society of America, 130, 440-460.
  25. Grossberg, S. and Pilly, P. (2011). A self-organizing hierarchical neural model of spatial navigation: Coordinated learning of entorhinal grid cells and hippocampal place cells. Hippocampus.
  26. Grossberg, S., Leveille, J. and Versace, M. (2011). How do object reference frames and motion vector decomposition emerge in laminar cortical circuits? Attention, Perception, & Psychophysics, 73, 1147-1170.
  27. Grossberg, S., Markowitz, J., and Cao, Y. (2011). On the road to invariant recognition: Explaining response properties of cells in inferotemporal cortex using multiple-scale task-sensitive attentive learning. Neural Networks, 24, 1036-1049.
  28. Grossberg, S., Mhatre, H., and Gorchetchnikov, A. (2011). Learning a dorsoventral gradient of grid cell receptive field sizes from a gradient of habituative rates in a self-organizing entorhinal cortical map.
  29. Grossberg, S., Pilly, P., and Mhatre, H. (2011). Learning a dorsoventral gradient of grid cell spatial scales in the entorhinal cortex by a self-organizing map. PLoS Computational Biology.
  30. Grossberg, S., Srinivasan, K., and Yazdanbakhsh, A. (2011). On the road to invariant object recognition: How cortical area V2 transforms absolute to relative disparity during 3D vision. Neural Networks, 24, 686-692.
  31. Guenther, F.H. and Vladusich, T. (2011). A neural theory of speech acquisition and production. Journal of Neurolinguistics.
  32. Ivery, R., Bullock, D., and Grossberg, S. (2011). A neural architecture for lookahead planning: Mentally simulating, segmenting, and storing the shortest path around obstacles to a goal.
  33. Ivey, R., Bullock, D., and Grossberg, S. (2011). A neuromorphic model of spatial lookahead planning. Neural Networks, 24, 257-266.
  34. Kazerounian, S. and Grossberg, S. (2011). Real-time speech category learning of working memory item sequences. Journal of the Acoustical Society of America.
  35. Livitz, G., Versace, M., Gorchetchnikov, A., Vasilkoski, Z., Ames, H., Chandler, B., Léveillé, J., and Mingolla, E (2011). Scalable adaptive brain-like systems. The Neuromorphic Engineer, 10, 10.2417/1201101.003500.
  36. Livitz, G., Yazdabakhsh, A., Eskew, R.T., and Mingolla, E. (2011). Perceiving opponent hues in color induction displays. Seeing and Perceiving, 24, 1-17.
  37. Maryott, J., Noyce, A., and Sekuler, R. (2011). Eye movements and imitation learning: Intentional disruption of expectation. Journal of Vision, 11, 1-16.
  38. Matthews, N., Gold, B., Sekuler, R., and Park, S. (2011). Gesture imitation in schizophrenia. Schizophrenia Bulletin.
  39. Raudies, F. and Hasselmo, M. (2011). Modeling boundary vector cell firing given optic flow as a cue. PLoS Computational Biology.
  40. Raudies, F. and Neumann, H. (2011). A review and evaluation of methods estimating ego-motion. Computer Vision and Image Understanding.
  41. Raudies, F., Mingolla, E., and Hasselmo, M. (2011). Modeling the influence of optic flow on grid cell firing in the absence of other cues. Journal of Computational Neuroscience.
  42. Raudies, F., Mingolla, E., and Neumann, H. (2011). A model of motion transparency processing with local center-surround interactions and feedback. Neural Computation, 23, 2868-2914.
  43. Raudies, F., Mingolla, E., and Neumann, H. (2011). Motion transparency and spatial integration size - a modeling study. Journal of Vision, 11, 977.
  44. Ross, R.S., LoPresti, M.L., Schon, K., and Stern, C.E. (2011). Orbitofrontal cortex links overlapping stimuli to the temporal context in which they appear during working memory.
  45. Schon, K., Ross, R.S., Hasselmo, M.E., and Stern, C.E. (2011). Complementary roles of medial temporal lobes and dorsolateral prefrontal vortex for working memory for novel and familiar trial-unique visual stimuli: An fMRI study.
  46. Silver, M.R., Grossberg, S., Bullock, D., Histed, M., and Miller, E. (2011). A neural model of sequential movement planning and control of eye movements: Item-order-rank working memory and saccade selection by the supplementary eye fields.
  47. Snider G., Amerson R., Carter D., Abdalla H., Qureshi S., Leveille J., Versace M., Ames H., Patrick S., Chandler B., Gorchetchnikov A., and Mingolla E. (2011). Adaptive computation with memristive memory. IEEE Computer, 44(2), 21-28.
  48. Snider, G., Amerson, R., Carter, D., Abdalla, H., Qureshi, M.S., Léveillé, J., Versace, M., Ames, H., Patrick, S., Chandler, B., Gorchetchnikov, A., and Mingolla, E. (2011). From synapses to circuitry: Using memristive memory to explore the electronic brain. IEEE Computer, 44, 21-28.
  49. Sohail, A., and Ames, H. (2011). Transforming robotics with biologically inspired learning models. Behind the Scenes, Online publication,, June 2011.
  50. Sternshen, H., Agam, Y., and Sekuler, R. (2011). EEG correlates of attentional tracking. PLoS ONE, e22660.
  51. Szalay, J.J., Morin, N.D., and Kantak, K.M. (2011). Involvement of the dorsal subiculum and rostral basolateral amygdala in cocaine cue extinction learning in rats. European Journal of Neuroscience, 33, 1299-1307.
  52. Szalay, J.J., Morin, N.D., Kantak, K.M. (2011). Involvement of the dorsal subiculum and rostral basolateral amygdala in cocaine cue extinction learning in rats. European Journal of Neuroscience, 33, 1299-1307.
  53. Taylor, J.G. and Cutsuridis, V. (2011). Cognitive Computation, Special Issue on Saliency, attention, visual search and picture scanning, in press.
  54. Wong, C. and Versace, M. (2011). Modeling financial time series with artificial neural networks. Global Journal of Business Research, 5, 27-43.
  55. Wong, C. and Versace, M. (2011). Context sensitivity with neural models in financial decision processes. Global Journal of Business Research.
  56. Yazdanbakhsh A. and Gori S. (2011). Mathematical analysis of Accordion Grating illusion: A differential geometry approach to introduce 3D aperture problem. Neural Networks.